BoonDock Tip : { Section - Python}
Do not initialise the empty String with quotes. Try to use 'None' in your projects. It is the best practices though.
sqlConnection=ββ ββ- Not good practice
sqlConnection=None β- Best practice
Do not initialise the empty String with quotes. Try to use 'None' in your projects. It is the best practices though.
sqlConnection=ββ ββ- Not good practice
sqlConnection=None β- Best practice
15 Websites To Follow As A Developer
1. Stackoverflow
2. Google
3. YouTube
4. DevDocs. io
5. Github
6. Freecodecamp
7. LeetCode
8. IndieHackers
9. Udemy
10. Hashnode
11. Medium
12. Dev. to
13. W3Schools
14. Codecademy
15. Hacker News
May be you have another list ππ
1. Stackoverflow
2. Google
3. YouTube
4. DevDocs. io
5. Github
6. Freecodecamp
7. LeetCode
8. IndieHackers
9. Udemy
10. Hashnode
11. Medium
12. Dev. to
13. W3Schools
14. Codecademy
15. Hacker News
May be you have another list ππ
πΈπ¬ - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
β’ High-performance Deep Learning models for Text2Speech tasks.
β¦ Text2Spec models (Tacotron, Tacotron2, Glow-TTS, SpeedySpeech).
β¦ Speaker Encoder to compute speaker embeddings efficiently.
β¦ Vocoder models (MelGAN, Multiband-MelGAN, GAN-TTS, ParallelWaveGAN, WaveGrad, WaveRNN)
β’ Fast and efficient model training.
β’ Detailed training logs on the terminal and Tensorboard.
β’ Support for Multi-speaker TTS.
β’ High-performance Deep Learning models for Text2Speech tasks.
β¦ Text2Spec models (Tacotron, Tacotron2, Glow-TTS, SpeedySpeech).
β¦ Speaker Encoder to compute speaker embeddings efficiently.
β¦ Vocoder models (MelGAN, Multiband-MelGAN, GAN-TTS, ParallelWaveGAN, WaveGrad, WaveRNN)
β’ Fast and efficient model training.
β’ Detailed training logs on the terminal and Tensorboard.
β’ Support for Multi-speaker TTS.
https://github.com/TheAlgorithms/Python/blob/master/DIRECTORY.md
One place where you can find hundreds of algorithms.
Even you can find them in another languages as well.
https://github.com/TheAlgorithms
One place where you can find hundreds of algorithms.
Even you can find them in another languages as well.
https://github.com/TheAlgorithms
GitHub
Python/DIRECTORY.md at master Β· TheAlgorithms/Python
All Algorithms implemented in Python. Contribute to TheAlgorithms/Python development by creating an account on GitHub.
Meet LAVIS - a one-stop library for language-and-vision research and applications!
π₯Github: https://github.com/salesforce/LAVIS
πTech Report: arxiv.org/abs/2209.09019
LAVIS features
- Unified and modular interface to access 10+ tasks, 20+ datasets, 30+ pre-trained models!
π₯Github: https://github.com/salesforce/LAVIS
πTech Report: arxiv.org/abs/2209.09019
LAVIS features
- Unified and modular interface to access 10+ tasks, 20+ datasets, 30+ pre-trained models!
π¦π¦All tools Data Engineers need! Categorized into cloud native (only available on that platform) and cloud agnostic (use anywhere) platforms & tools on the top. On the left you find categories and subcategories for the tools.
ππThe goal for every engineer is to at least have knowledge of one tool in every category (row).
ππAs example:
- If you are on Azure then learn when and how to use for at least one of the tools in every row of Azure
- Or go fully cloud agnostic and open source. It's your choice.
- You can also combine cloud agnostic with cloud platforms together by replacing the cloud native tools of one row with a cloud agnostic one.
π€·ββοΈ thatβs it man π¨!!
ππThe goal for every engineer is to at least have knowledge of one tool in every category (row).
ππAs example:
- If you are on Azure then learn when and how to use for at least one of the tools in every row of Azure
- Or go fully cloud agnostic and open source. It's your choice.
- You can also combine cloud agnostic with cloud platforms together by replacing the cloud native tools of one row with a cloud agnostic one.
π€·ββοΈ thatβs it man π¨!!
π¦π¦βοΈβοΈ
OpenAI trained and are open-sourcing a neural net called Whisper that approaches human level robustness and accuracy on English speech recognition.
Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web.
https://openai.com/blog/whisper/
Check out above link for paper, code and more details
π½π½
OpenAI trained and are open-sourcing a neural net called Whisper that approaches human level robustness and accuracy on English speech recognition.
Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web.
https://openai.com/blog/whisper/
Check out above link for paper, code and more details
π½π½
βοΈβοΈWhat is πππ₯π’ππ«πππ’π¨π§ π’π§ ππππ‘π’π§π ππππ«π§π’π§π ?
πCalibration is the property that tells us how well the estimated probabilities of a model match the actual probabilities, a.k.a the observed frequency of occurrences.
πCalibration can be represented using the Brier score. The Brier score is nothing more than the MSE between the actual and the estimated probabilities.
πThe two most common methods to address poor calibration is:
πplatt scaling and
πisotonic regression
πCalibration is the property that tells us how well the estimated probabilities of a model match the actual probabilities, a.k.a the observed frequency of occurrences.
πCalibration can be represented using the Brier score. The Brier score is nothing more than the MSE between the actual and the estimated probabilities.
πThe two most common methods to address poor calibration is:
πplatt scaling and
πisotonic regression
=======================================
βοΈβοΈVisual explanations of core machine learning concepts.
=======================================
πNothing can beat the use of infographics and interactivity when explaining some concept,
πFor Linear Regression
https://mlu-explain.github.io/linear-regression/
πFor all,
https://mlu-explain.github.io/
βοΈβοΈVisual explanations of core machine learning concepts.
=======================================
πNothing can beat the use of infographics and interactivity when explaining some concept,
πFor Linear Regression
https://mlu-explain.github.io/linear-regression/
πFor all,
https://mlu-explain.github.io/
This media is not supported in your browser
VIEW IN TELEGRAM
π«₯π«₯FLAG: Flow-based 3D Avatar Generation from Sparse Observations
πPaper :
https://microsoft.github.io/flag/files/paper.pdf
πLink :
https://www.microsoft.com/en-us/research/publication/flag-flow-based-3d-avatar-generation-from-sparse-observations/
πPaper :
https://microsoft.github.io/flag/files/paper.pdf
πLink :
https://www.microsoft.com/en-us/research/publication/flag-flow-based-3d-avatar-generation-from-sparse-observations/
𧬠The data structure for unstructured multimodal data · Neural Search · Vector Search · Document Store
For doc
https://docarray.jina.ai/
For GitHub
https://github.com/jina-ai/docarray
For doc
https://docarray.jina.ai/
For GitHub
https://github.com/jina-ai/docarray
Transformers in Time Series: A Survey
A curated list of awesome resources (papers, code, data) on Transformers in Time Series categorized by tasks, including:
β’ Forecasting
β’ Anomaly detection
β’ Classification
Transformers capture long-range dependencies and interactions.
abs: https://arxiv.org/abs/2202.07125
pdf: https://arxiv.org/pdf/2202.07125.pdf
Awesome list repo: https://github.com/qingsongedu/time-series-transformers-review
A curated list of awesome resources (papers, code, data) on Transformers in Time Series categorized by tasks, including:
β’ Forecasting
β’ Anomaly detection
β’ Classification
Transformers capture long-range dependencies and interactions.
abs: https://arxiv.org/abs/2202.07125
pdf: https://arxiv.org/pdf/2202.07125.pdf
Awesome list repo: https://github.com/qingsongedu/time-series-transformers-review
googlefinance
Python module to get stock data from Google Finance API. This module provides no delay, real time stock data in NYSE & NASDAQ.
$pip install googlefinance
https://github.com/hongtaocai/googlefinance
Python module to get stock data from Google Finance API. This module provides no delay, real time stock data in NYSE & NASDAQ.
$pip install googlefinance
https://github.com/hongtaocai/googlefinance
GitHub
GitHub - hongtaocai/googlefinance: Python module to get real-time stock data from Google Finance API
Python module to get real-time stock data from Google Finance API - hongtaocai/googlefinance